High speed materials sorting using x-ray fluorescence

ABSTRACT

A system and process for classifying a piece of material of unknown composition at high speeds, where the system connected to a power supply. The piece is irradiated with first x-rays from an x-ray source, causing the piece to fluoresce x-rays. The fluoresced x-rays are detected with an x-ray detector, and the piece of material is classified from the detected fluoresced x-rays. Detecting and classifying may be cumulatively performed in less than one second. An x-ray fluorescence spectrum of the piece of material may be determined from the detected fluoresced x-rays, and the detection of the fluoresced x-rays may be conditioned such that accurate determination of the x-ray fluorescence spectrum is not significantly compromised, slowed or complicated by extraneous x-rays. The piece of material may be classified by recognizing the spectral pattern of the determined x-ray fluorescence spectrum. The piece of material may be flattened prior to irradiation and detection. The x-ray source may irradiate the first x-rays at a high intensity, and the x-ray source may be an x-ray tube.

RELATED APPLICATION

This application is a continuation, claiming the benefit under 35 U.S.C.§120, of U.S. application Ser. No. 12/605,623, titled “High SpeedMaterials Sorting Using X-ray Fluorescence,” filed Oct. 26, 2009,currently pending, which is a continuation of U.S. application Ser. No.12/138,927, filed Jun. 13, 2008, issued Nov. 10, 2009 as U.S. Pat. No.7,616,733, titled “High Speed Materials Sorting Using X-rayFluorescence,” which is a continuation of U.S. application Ser.No.11/357,432, titled “High Speed Materials Sorting Using X-rayFluorescence,” filed Feb. 17, 2006, now abandoned, which is acontinuation of U.S. application Ser. No. 11/232,574, titled “High SpeedMaterials Sorting Using X-Ray Fluorescence”, filed Sep. 22, 2005, nowabandoned, which is a continuation of U.S. application Ser. No.10/967,981, titled “High Speed Materials Sorting Using X-RayFluorescence”, filed Oct. 19, 2004, now abandoned, which is acontinuation of U.S. application Ser. No. 10/364,783, titled “High SpeedMaterials Sorting Using X-Ray Fluorescence”, filed Feb. 11, 2003, issuedMay 3, 2005 as U.S. Pat. No. 6,888,917, which is a continuation of U.S.patent application Ser. No. 09/827,784, titled “High Speed MaterialsSorting Using X-Ray Fluorescence”, filed Apr. 6, 2001, issued Feb. 11,2003 as U.S. Pat. No. 6,519,315, which is a continuation of U.S. patentapplication Ser. No. 09/400,491 titled, “High Speed Materials SortingUsing X-Ray Fluorescence”, filed Sep. 21, 1999, issued Jul. 24, 2001 asU.S. Pat. No. 6,266,390, which claims priority under 35 U.S.C. §119(e)to U.S. provisional application Ser. No. 60/101,128, titled “ElectronicsSortation for Recycling of Post Consumer Non-Ferrous Metals,” filed Sep.21, 1998, where each application is hereby incorporated by reference inits entirety.

GOVERNMENT LICENSE RIGHTS

The U.S. Government has a paid-up license in this invention and theright in limited circumstances to require the patent owner to licenseothers on reasonable terms as provided for by the terms of Grant No.DMI-9761412 awarded by the National Science Foundation.

This invention was made with Government support under Grant No.DMI-9761412 awarded by the National Science Foundation. The Governmenthas certain rights in this invention.

FIELD OF THE INVENTION

This invention relates to a system and process for sorting pieces ofmaterials (by composition) in a stream of materials moving along aconveyor belt. Particularly, this invention relates to a system andprocess for classifying pieces of materials of unknown composition basedon the x-ray fluorescence spectrum of each respective piece so as topermit very high speed sorting of the unknown materials.

BACKGROUND OF THE INVENTION

Current worldwide environmental concerns have fueled an increase inefforts to recycle used equipment and articles containing materials thatcan be reused. Such efforts have produced new and improved processes forsorting materials such as plastics, glass, metals, and metal alloys.

As used herein, a “material” may be a chemical element, a compound ormixture of chemical elements, or a compound or mixture of a compound ormixture of chemical elements, wherein the complexity of a compound ormixture may range from being simple to complex. Materials may includemetals (ferrous and non-ferrous), metal alloys, plastics, rubber, glass,ceramics, etc. As used herein, element means a chemical element of theperiodic table of elements, including elements that may be discoveredafter the filing date of this application.

Generally, methods for sorting pieces of materials involve determining aphysical property or properties of each piece, and grouping togetherpieces sharing a common property or properties. Such properties mayinclude color, hue, texture, weight, density, transmissivity to light,sound, or other signals, and reaction to stimuli such as various fields.Methods to determine these properties include visual identification of amaterial by a person, identification by the amount and/or wavelength ofthe light waves emitted or transmitted, eddy-current separation,heavy-media plant separation, and x-ray fluorescence detection.

With respect to metals and metal alloys, today it is neither technicallynor commercially feasible to separate and recover many of thenon-ferrous metals that are manufactured into products and discarded atthe end of their useful life. In residential waste, only aluminum cansare recycled to any significant degree. Virtually none of the othernon-ferrous materials in our residential waste are recovered. Instead,they are disposed in landfills. Further, small non-ferrous materialsbelow ⅝ inches in size are landfilled from nearly 200 automobileshredders.

Smaller-sized pieces of non-ferrous metals from automobile shredders arenot separated because their recovery is not cost-effective. They canonly be consolidated and shipped to larger facilities for furtherprocessing. Mixed non-ferrous metals from industrial processes are oftendisposed or junked because hand-sorting and small-particle recoverytechnologies either do not work well or are not cost-effective. Nearly 2billion pounds of valuable non-ferrous metals are discarded in landfillsevery year in the U.S. alone. Worldwide, the amount of metal wasted isfar greater. If this metal could be economically recycled at highvolumes, the potential value generated is estimated to be in excess of 1billion dollars (U.S.) per year. Further, there are approximately 200waste-to-energy facilities, 200 automobile shredders, and thousands ofmetal scrap yards in the U.S. alone that could benefit financially (andotherwise) from an improved sorting system.

X-ray fluorescence spectroscopy has long been a useful analytical toolin the laboratory for classifying materials by identifying elementswithin the material, both in academic environments and in industry. Theuse of characteristic x-rays such as, for example, K-shell or L-shellx-rays, emitted under excitation provides a method for positiveidentification of elements and their relative amounts present indifferent materials, such as metals and metal alloys. For example,radiation striking matter causes the emission of characteristic K-shellx-rays when a K-shell electron is knocked out of the K-shell by incomingradiation and is then replaced by an outer shell electron. The outerelectron, in dropping to the K-shell energy state, emits x-ray radiationcharacteristics of the atom.

The energy of emitted x-rays depends on the atomic number of thefluorescing elements. Energy-resolving detectors can detect thedifferent energy levels at which x-rays are fluoresced, and generate anx-ray signal from the detected x-rays. This x-ray signal may then beused to build an energy spectrum of the detected x-rays, and from theinformation, the element or elements which produced the x-rays may beidentified. Fluorescent x-rays are emitted isotopically from anirradiated element and the detected radiation depends on the solid anglesubtended by the detector and any absorption of this radiation prior tothe radiation reaching the detector. The lower the energy of an x-ray,the shorter the distance it will travel before being absorbed by air.Thus, when detecting x-rays, the amount of x-rays detected is a functionof the quantity of x-rays emitted, the energy level of the emittedx-rays, the emitted x-rays absorbed in the transmission medium, theangles between the detected x-rays and the detector, and the distancebetween the detector and the irradiated material.

Although x-ray spectroscopy is a useful analytical tool for classifyingmaterials, with current technology, the cost is high per analysis, andthe time required is typically minutes or hours. Scrap yardidentification of metals and alloys is primarily accomplished today bytrained sorters who visually examine each metal object one at a time.Contamination is removed by shearing. A trained sorter observes subtlecharacteristics of color, hue, texture, and density to qualitativelyassess the composition of the metal. Sometimes, spark testing orchemical “litmus” testing aids in identification. The process is slowand inaccurate, but is the most common method in existence today forsorting scrap metal to upgrade its value.

There have been disclosed a variety of systems and techniques forclassifying materials based on the x-ray fluorescence of the material.Some of these systems involve hand-held or bench-top x-ray fluorescencedetectors. Some of these systems include serially conveying pieces ofmaterial along a conveyor belt and irradiating each piece, in turn, withx-rays. These x-rays cause each piece of material to fluoresce x-rays atvarious energy levels, depending on the elements contained in the piece.The fluoresced x-rays are detected, and the piece of material is thenclassified based on the fluoresced x-rays and sorted in accordance withthis classification.

Such disclosed systems, however, have not been widely acceptedcommercially because they require about one second or more to detect thex-rays and accurately classify the piece of material accordingly, andthey are expensive relative to the number of objects identified per unittime.

SUMMARY OF THE INVENTION

In response to the need for faster classification, disclosed herein is asystem and process for classifying a piece of material based on thex-ray fluorescence of its constituents, wherein x-rays are detected fromthe piece and the piece is accurately classified, cumulatively, insubstantially less than a second—indeed, typically in about 100milliseconds (ms) or less.

To achieve these speeds, a high intensity x-ray source, such as an x-raytube, is used to irradiate the piece. The previously mentioned systems,by contrast, employ a comparatively low-power narrow-spectrum x-raysource such as, for example, Cadmium isotope Cd¹²⁹, Americium isotopeAm²⁴¹, Cobalt isotope Co⁵⁷, and Iron isotope Fe⁵⁵. Although use of anx-ray tube has been mentioned as a possible alternative x-ray source fora material sorting system, a high intensity x-ray source has not beenimplemented by others in such systems, and there are major problems indoing so that have not previously been resolved. Consequently, therepreviously has not been shown a system that enables use of a highintensity x-ray source in such a system.

Another problem with many known material sorting systems that classifypieces of material based on the x-ray fluorescence of the material isthat such systems are limited to analyzing only the fluorescence ofspecific, predetermined elements of interest in the piece of material.Analyzing only select fluorescence limits the accuracy of theidentification and the range of materials that can be identified.

In response to this problem, there is also disclosed herein a system andprocess for classifying a piece of material based on the x-rayfluorescence of the piece by recognizing a broad spectral pattern of thex-ray fluorescence.

According to the invention, a high speed process for classifying a pieceof material of unknown composition is provided. The piece is irradiatedwith x-rays from an x-ray source, causing the piece to fluoresce x-rays.The fluoresced x-rays are detected with an x-ray detector and the pieceis classified from the detected fluoresced x-rays.

In optional illustrative embodiments, detecting and classifying arecumulatively performed in less than one second, less than 500 ms, lessthan 100 ms, less than 50 ms, and preferably even less than 15 ms.

Preferably, but optionally, an x-ray fluorescence spectrum of the pieceof material from the detected fluoresced x-rays is determined, and atleast one of the steps of the irradiating and detecting includesconditioning the irradiating x-rays or the fluoresced x-rays,respectively, such that speed and accuracy of determining the x-rayfluorescence spectrum is not significantly compromised or complicated bygeneration or detection of extraneous x-rays.

In yet another optional aspect, the irradiating x-rays are filtered toreduce a number of irradiating x-rays having an energy level too low tocause the piece to fluoresce x-rays having an energy level within apredefined range of the x-ray fluorescence spectrum.

In still another optional aspect, the irradiating x-rays are aimed atthe piece of material to reduce an amount of x-rays detected by thex-ray detector that were not fluoresced by the piece itself.

In still another optional aspect of the illustrated embodiments, thex-ray fluorescence spectrum is determined for a predefined range ofenergy levels, and the irradiating x-rays are aimed by collimating thex-ray source with a collimator whose aperture components are madesubstantially of one or more materials that fluoresce at energy levelsnot within the predefined range.

For example, the operative parts of the collimator may be formedessentially of polyvinyl chloride.

In another optional aspect, the x-ray source is aimed at the piece ofmaterial with a small aperture to substantially confine the x-raysdetected by the x-ray detector to those fluoresced by the piece andlimit detection of other x-rays.

In another optional aspect, the x-ray detection is aimed by collimatingthe x-ray detector with a collimator consisting essentially of one ormore materials that fluoresce at energy levels not within the predefinedrange. For example, the collimator may be formed essentially ofpolyvinyl chloride.

In yet another optional aspect, the piece of material is conveyed on aconveyor through a detection area where the irradiating x-rays irradiatethe piece and the fluoresced x-rays are detected from the piece. Theconveyor may be formed essentially of one or more materials thatfluoresce at energy levels not within the predefined energy range, sothat the conveyor does not fluoresce x-rays that significantly interferewith determination of the x-ray fluorescence spectrum of the piece.

In another optional aspect, the spectral pattern of the determined x-rayfluorescence spectrum is recognized.

In still another optional aspect, a plurality of x-ray fluorescencespectra are stored as reference spectra on a computer-readable medium,each reference spectrum having a spectral pattern and corresponding to adifferent material classification. Recognizing the detected spectralpattern includes comparing the determined x-ray fluorescence spectrum toeach of the reference spectra to determine which reference spectrum hasa spectral pattern most similar to the spectral pattern of thedetermined x-ray fluorescence spectrum. The piece of material isclassified as the material classification corresponding to the referencespectrum determined to have the most similar spectral pattern.

In a further optional aspect, the piece of material is conveyed on aconveyor and through a detection area where the irradiating x-raysirradiate the piece and the fluoresced x-rays are detected from thepiece, and an ejector corresponding to the classification of the pieceis actuated such that the piece is ejected from the conveyor at a pointdownstream from the detection area and associated with saidclassification.

In another optional aspect, the piece of material is flattened prior toirradiation and detection.

In still another optional aspect, the step of irradiating includesirradiating the x-rays at a high intensity.

Optionally, but preferably, the x-ray source is an x-ray tube.

It will be appreciated that both large and small pieces may beprocessed, including pieces having a largest dimension less than ⅝ inch;indeed, even less than approximately ¼ inch.

In another illustrative embodiment, a system for classifying a piece ofmaterial of unknown composition is provided, where the system isconnected to a power supply. An x-ray source powered by the power supplygenerates x-rays that irradiate the piece of material, causing the pieceto fluoresce x-rays. An x-ray detector detects the fluoresced x-rays andproduces as an output a signal, called an x-ray signal, representing thedetected x-rays. An x-ray fluorescence processing module is connected tothe x-ray detector. The processing module receives as an input the x-raysignal and generates as an output a classification signal thatidentifies the classification of the piece of material.

In optional aspects, the x-ray detector and x-ray fluorescenceprocessing module are operative to detect the fluoresced x-rays andclassify the piece, respectively, in a combined time less than onesecond, less than 500 ms, less than 100 ms, less than 50 ms, andpreferably even less than 15 ms.

In yet another optional aspect, the x-ray fluorescence processing moduleincludes a spectrum acquisition module connected to the x-ray detector,the spectrum acquisition module receives as an input the x-ray signaland generates as an output an x-ray fluorescence spectrum, and aclassification module receives as an input the x-ray fluorescencespectrum and generates as an output a classification signal indicating aclassification of the piece of material. The system is conditioned suchthat accurate determination of the x-ray fluorescence spectrum is notsignificantly compromised or complicated by generation or detection ofextraneous x-rays.

In another optional aspect of this embodiment, the x-ray fluorescencespectrum is determined for a predefined range of energy levels, and anx-ray filter filters the irradiating x-rays to reduce a number ofirradiating x-rays having an energy level too low to cause the piece tofluoresce x-rays having an energy level within the predefined range ofthe x-ray fluorescence spectrum.

In another optional aspect the output of the x-ray source is conditionedby a collimator, the collimator having an aperture to aim theirradiating x-rays at the piece such that production of x-rays fromobjects other than the piece is reduced.

In an optional feature of this aspect, the x-ray fluorescence spectrumis determined for a predefined range of energy levels, aperturecomponents of the collimator being made substantially of one or morematerials that fluoresce at energy levels not within the predefinedrange.

For example, the collimator may be formed essentially of polyvinylchloride.

In another optional aspect, the x-rays detected by the x-ray detectorare conditioned by a collimator, the collimator having an aperture toaim the detection of the fluoresced x-rays at the piece during thedetection such that detection of incident radiation from objects otherthan the piece is minimized

For example, the collimator may be formed essentially of polyvinylchloride.

In still another optional aspect, the x-ray fluorescence spectrum isdetermined for a predefined range of energy levels, and a conveyorconveys the piece of material through a detection area where theirradiating x-rays irradiate the piece and the fluoresced x-rays aredetected from the piece, and the conveyor consists essentially of one ormore materials that fluoresce at energy levels not within the predefinedrange.

For example, the conveyor belt may be formed essentially of polyvinylchloride.

In another optional aspect, the x-ray fluorescence processing moduleincludes a spectrum acquisition module connected to the x-ray detector,the spectrum acquisition module to receive as an input the x-ray signaland to generate as an output an x-ray fluorescence spectrum, and aclassification module to receive as an input the x-ray fluorescencespectrum and to generate as an output a classification signal thatindicates the classification of the piece, wherein the classificationmodule is operative to classify the piece by recognizing a spectralpattern of the x-ray fluorescence spectrum.

In yet another optional aspect, a computer-readable storage mediumstores a plurality of x-ray fluorescence spectra as reference spectra,each reference spectrum having a spectral pattern and corresponding to adifferent material classification, and the classification module furtherincludes means for comparing the determined x-ray fluorescence spectrumto each of the reference spectra to determine which reference spectrumhas a spectral pattern most similar to the spectral pattern of thedetermined x-ray fluorescence spectrum. The classification of the piececorresponds to the reference spectrum determined to have the mostsimilar spectral pattern.

In a further optional aspect, a conveyor conveys the piece of materialthrough a detection area where the irradiating x-rays irradiate thepiece and the fluoresced x-rays are detected from the piece, and anejector corresponding to the classification of the piece having an inputreceives an ejection signal, and the ejector ejects the piece from theconveyor in accordance with the ejection signal at a point downstreamfrom the detection area and associated with said classification.

In another optional aspect, the piece of material is flattened prior toirradiation and detection.

In still another optional aspect, the x-ray source is operative togenerate the irradiating x-rays at a high intensity.

Optionally, but preferably, the x-ray source is an x-ray tube.

In another illustrative embodiment, a system for classifying a piece ofmaterial of unknown composition at high speeds is provided. The systemincludes means for irradiating the piece with x-rays from an x-raysource, causing the piece to fluoresce x-rays, means for detecting thefluoresced x-rays with an x-ray detector, and means for classifying thepiece of material from the detected fluoresced x-rays.

In optional illustrative embodiments, the means for detecting and meansfor classifying are operative to detect the fluoresced x-rays andclassify the piece, respectively, in a combined time of less than onesecond, less than 500 ms, less than 100 ms, less than 50 ms, andpreferably even less than 15 ms.

Preferably, but optionally, the system includes means for determining anx-ray fluorescence spectrum of the piece of material from the detectedfluoresced x-rays, and means for conditioning at least one of theirradiating x-rays and the fluoresced x-rays, respectively, such thatspeed and accuracy of determining the x-ray fluorescence spectrum is notsignificantly compromised or complicated by generation and detection ofextraneous x-rays.

In yet another optional aspect, the means for conditioning includesmeans for filtering the irradiating x-rays to reduce a number ofirradiating x-rays having an energy level too low to cause the piece tofluoresce x-rays having an energy level within a predefined range of thex-ray fluorescence spectrum.

In another optional aspect of the illustrated embodiments, the means forconditioning includes means for aiming the irradiating x-rays at thepiece of material to reduce an amount of x-rays detected by the x-raydetector that were not fluoresced by the piece itself.

Preferably, but optionally, the means for aiming includes a collimatorwhose aperture components are made substantially of one or morematerials that fluoresce at energy levels not within the predefinedrange.

For example, operative parts of the collimator may be formed essentiallyof polyvinyl chloride.

In another optional aspect, the means for conditioning includes meansfor aiming the x-ray detector at the piece of material to substantiallyconfine the x-rays detected by the x-ray detector to those fluoresced bythe piece and limit detection of other x-rays.

In another optional aspect, the x-ray fluorescence spectrum isdetermined for a predefined range of energy levels, and the means foraiming the x-ray detector includes a collimator whose aperturecomponents are made of one or more materials that fluoresce at energylevels not within the predefined range.

For example, operative parts of the collimator may be formed essentiallyof polyvinyl chloride.

In yet another optional aspect, the system further includes means forconveying the piece of material through a detection area where theirradiating x-rays irradiate the piece and the fluoresced x-rays aredetected from the piece, and the means for conveying includes a conveyorthat may be formed essentially of one or more materials that fluoresceat energy levels not within the predefined energy range of thedetermined x-ray fluorescence spectrum so that the conveyor does notfluoresce x-rays that significantly interfere with determination of thex-ray fluorescence spectrum of the piece.

In an optional aspect, the conveyor is made essentially of polyvinylchloride.

In still another optional aspect, the system further includes means forrecognizing the spectral pattern of the determined x-ray fluorescencespectrum, and the means for classifying the piece base theclassification on the recognition of the spectral pattern.

In another optional aspect, the means for detecting, means fordetermining, means for recognizing, and means for classifying areoperative to detect the fluoresced x-rays, determine the x-rayfluorescence spectrum, recognize the spectral pattern of the x-rayfluorescence spectrum, and classify the piece, respectively, in acombined time of less than one second.

In a further optional aspect, the system further includes means forstoring a plurality of x-ray fluorescence spectra as reference spectraon a computer-readable medium, each reference spectrum having a spectralpattern and corresponding to a different material classification, andthe means for recognizing the detected spectral pattern includes meansfor comparing the determined x-ray fluorescence spectrum to each of thereference spectra to determine which reference spectrum has a spectralpattern most similar to the spectral pattern of the determined x-rayfluorescence spectrum, and the piece of material is classified as thematerial classification corresponding to the reference spectrumdetermined to have the most similar spectral pattern.

In yet another optional aspect, the system further includes means forflattening the piece of material prior to irradiation and detection.

In still another optional aspect, the system further includes means forirradiating the x-rays at a high intensity.

Optionally, but preferably, the x-ray source is an x-ray tube.

In another optional aspect, the system further includes means forconveying the piece of material through a detection area where theirradiating x-rays irradiate the piece and the fluoresced x-rays aredetected from the piece, and means for actuating an ejectorcorresponding to the classification of the piece such that the piece isejected from the conveying means at a point downstream from thedetection area and associated with said clarification.

These and other features and advantages of the invention will be morereadily understood and appreciated from the detailed description below,which should be read together with the accompanying drawing figures.

BRIEF DESCRIPTION OF THE DRAWINGS

In the drawings:

FIG. 1 is a diagram showing an illustrative embodiment of a high speedmaterial sorting system;

FIGS. 2A and 2B are a flow chart showing an illustrative embodiment of aprocess of sorting pieces of material at high speed;

FIG. 3 is a diagram showing an illustrative embodiment of an x-raydetection chamber of a high speed material sorting system;

FIG. 4 is a block diagram showing an illustrative embodiment of an x-rayfluorescence processing module;

FIG. 5 is a data flow diagram showing an illustrative embodiment of thefunction of a spectrum acquisition module;

FIG. 6 is a flow chart showing an illustrative embodiment of a processfor classifying a piece of material based on the x-ray fluorescencespectrum of the piece;

FIG. 7A is a diagram showing an illustrative embodiment of using anenergy histogram to represent an x-ray fluorescence spectrum;

FIG. 7B is a diagram showing an illustrative embodiment of using anenergy histogram to represent an x-ray fluorescence spectrum;

FIG. 8 is a screen capture of an illustrative embodiment of a userinterface for analyzing detected x-ray fluorescence spectra; and

FIG. 9 is a block diagram showing an illustrative embodiment of aprocess of binary sorting materials.

DETAILED DESCRIPTION

The combination of the high speed x-ray irradiation and detectiontechniques and the execution of a complex sorting algorithm describedherein permit highly accurate classification and sorting of materials atvery fast rates, at least one to two orders of magnitude faster thancurrently used techniques.

FIG. 1 depicts an illustrative embodiment of a high speed materialsorting system. A materials singulator and feeder 3 feeds a singulatedstream of pieces of material 11 onto a conveyor belt 5. The conveyorbelt 5 receives the pieces of material 11 and conveys the pieces ofmaterial through an x-ray detection chamber 7 downstream to be sortedinto sorting bins 18-23. Although a conveyor belt is used in theillustrative embodiment of FIG. 1, any suitable conveying means may beused.

An x-ray detection chamber 7 receives each piece of material, irradiatesthe material with x-rays, and detects the x-ray fluorescence (xrf) fromthe materials as a result of the irradiation. The detection chamber 7 isalso connected to an xrf processing module 9 through a signal carrier 8such as, for example, a data bus. The xrf processing module 9 receives asignal representing the xrf detected from a piece of material along thesignal carrier 8. The xrf processing module 9 then classifies the pieceof material based on the xrf signature of the material, and activates asorting device such as an air jet—for example, one of the air jets13-17—that is mapped or assigned to the classification. When one of theair jets 13-17 receives a signal from the xrf processing module 9, thatair jet emits a stream of air that causes a piece of material to beejected from the conveyor belt 5 into a sorting bin corresponding tothat air jet such as, for example, one of the sorting bins 18-22. Highspeed air valves from Mac Industries may be used, for example, to supplythe jets with air pressure at, for example, 60-90 psi, withoperating/closing times of 15 ms.

Although air jets are used to eject materials in the illustrativeembodiment of FIG. 1, other methods may be used to eject the pieces ofmaterial, such as robotically removing the piece of material from belt5, pushing the piece of material from belt 5, or causing an opening inthe belt from which a piece of material may drop.

In addition to sorting bins 18-22, into which pieces of material areforced, the system 1 may also include a sorting bin 23 that receivespieces of material not forced from the belt 5. A piece of material maynot be ejected from the belt 5 when the classification of the piece isnot determined Thus, sorting bin 23 may serve as a default bin intowhich unclassified pieces of materials are dumped. Alternatively,sorting bin 23 may be used to receive one or more classifications ofpieces of material by deliberately not assigning any of the sorting bins18-22 to the one or more classifications. This technique of defaultsorting can be particularly useful in sorting materials which fluoresceat low energy levels difficult to detect because of absorption by airsuch as, for example, aluminum.

Depending upon the classifications of materials desired, multipleclassifications may be mapped to a single air jet and sorting bin. Inother words, there need not be a one-to-one correlation betweenclassifications and sorting bins. For example, it may be commerciallybeneficial to sort copper and brass into the same sorting bin. Toaccomplish this sort, when a piece of material is classified as eithercopper or brass, the same air jet may be activated to sort both copperand brass into the same sorting bin. The contents of this sorting binmay, for example, then be used to create a copper/brass alloy. Suchcombination sorting may be applied to produce any desired combination ofmaterial pieces and element distribution. The mapping of classificationsmay be programmed in the sorting application 35 of FIG. 4 to producesuch desired combinations.

The classifications of pieces are user-definable and not limited to anyknown classification of materials. The classifications may be defined byusing appropriate reference spectra, and programming the thresholdvalues for these spectra, as is described in more detail below inconnection with FIGS. 4 and 6. For example, the classification may bebetween: plastics, ceramics, glass, and, metals, such classificationhaving a relatively broad scope; different metals and metal alloys suchas, for example, zinc, copper, brass, chromeplate, and aluminum, suchclassification having a narrower scope; or between specific grades ofsteel, such classification having a relatively narrow scope. Thus, theclassifications may be programmed to distinguish between materials ofsignificantly different compositions such as, for example, plastics andmetal alloys, or to distinguish between materials of almost identicalcomposition such as, for example, different grades of steel.

Although FIG. 1 shows an illustrative embodiment of a high speedmaterial sorting system in which the pieces of materials 11 are conveyedalong a straight and level path, the system described herein is notlimited to such an embodiment. In an alternative embodiment, theconveyor belt 5 may be divided into multiple belts in series such as,for example, two belts, where a first belt conveys the materials intothe detection chamber 7, and a second belt conveys the pieces ofmaterial from the detection chamber 7. For example, the second belt maybe at a lower height than the first belt, such that pieces of material11 fall from the first belt onto the second belt through the detectionchamber.

In an illustrative embodiment, an x-ray detector and x-ray source may bearranged such that the irradiation of x-rays onto or detected from thebelt(s) is kept to a minimum (i.e., an acceptably low level), thusreducing detection of extraneous x-rays from the belt(s). (This bothimproves the speed and accuracy of classification as well as avoids“flooding” the detection needlessly.) In yet another embodiment, duringconveyance through the detection area each piece of material may be slidacross a window of material or air gap that allows x-rays to passthrough, with the x-ray source situated to irradiate x-rays through thewindow.

In another illustrative embodiment, the part of the conveyer beltdownstream from the detection chamber may be replaced by a circularconveyor, and the air jets 13-17, or other suitable removal means,arranged along the exterior or interior of the circular conveyor. In anoptional aspect of this illustrative embodiment, the entire conveyorbelt 5 is a circular conveyor, where the pieces of materials are fedonto the conveyer, and a detection chamber is located at a point alongthe conveyor.

In another illustrative embodiment of the high speed material sortingsystem, gravity may be used to accelerate the speed of the pieces ofmaterials. For example, the conveying belt may convey pieces of materialonto a surface that slopes downward leading toward the detection chamber7. Further, at some point along the path of conveyance, the pieces ofmaterials may be dropped into free fall, and be irradiated during freefall from an x-ray source or sources located along the sides. Thefluoresced x-rays could also be detected during free fall from an x-raydetector or detectors located along the path of trajectory. Althoughsuch an arrangement reduces background radiation, the detection processbecomes more complex. The location and speed of each falling piece mustbe detected to properly time the sorting process (constant speed cannotbe assumed as in the previously discussed embodiments). Further, theinherent unstable nature of pieces rolling down a slope or in free fallintroduces a variable element into the sorting process.

The system and process for classifying described herein may be appliedto a handheld system for classifying pieces of material one at a time.In such a system, adjustments would have to be made for portability, butthe general methods described herein for irradiating with x-rays,detecting fluoresced x-rays, building an xrf spectrum, and recognizing aspectral pattern of the xrf spectrum may be used.

FIGS. 2A and 2B is a flow chart depicting an exemplary illustrativeembodiment of a process of sorting materials at high speeds. First, instep 51, materials are fed in a singulated stream onto a conveyor belt.In an optional aspect of this illustrative embodiment, the materials areflattened with a flattening apparatus before being fed onto the conveyorbelt 5. For example, a rolls crusher may be used for this purpose.

By flattening the piece of material, any other materials adhered to thepiece of material may be removed. Further, flattening a piece ofmaterial before feeding the piece onto the conveyor belt improvessorting and classification of the materials. First, flattened pieces ofmaterial remain stationary on the conveyor belt, and do not roll. Thus,in the illustrative embodiment of FIG. 1, when a piece of material isclassified, and an appropriate air jet 13-17 is actuated, the piece isin a position anticipated by the xrf processing module 9, and the pieceis ejected from the conveyor belt into the appropriate sorting bin18-22. Second, flattening the pieces of material provides a largersurface area to irradiate and from which to detect x-rays. Consequently,the piece of material is bombarded with and fluoresces more x-rays,resulting in a more complete xrf spectrum being determined for the pieceof material. Third, the composition of the piece of material is lessinfluenced by surface contaminants. Because during flattening, freshmaterial surfaces are exposed, a cleaner xrf spectrum is produced.Consequently, the spectra detected are more representative of the pieceof material and not other materials that may be adhering to the surfaceof the piece of material.

In an illustrative embodiment, the conveyor belt 5 is depressed ortroughed in the center such that pieces of materials gravitate to thecenter of the conveyor belt 5, where they remain more stationary and maybe aligned directly beneath a detector.

Next, in step 53, the materials are conveyed along the conveyor belt andinto an x-ray detection chamber. In an illustrative embodiment, eachpiece is flattened while being conveyed along the belt, as discussedabove in connection with step 51.

In an illustrative embodiment, the belt is comprised at least mostly ofa material such as, for example, polyvinyl chloride (PVC), that whenirradiated, fluoresce x-rays only at low energy levels, as will bedisclosed in more detail with connection to FIG. 4. The speed at whichthe belt is operated is programmed in accordance with the spacingbetween the pieces of material and the cumulative time which it takesto: acquire or detect the x-rays from a piece of material; determine anxrf spectrum; and classify the piece. Such speeds may exceed 100 inchesper second.

In step 55, when a piece of material has entered the x-ray detectionchamber, the piece is irradiated with x-rays, as will be discussed belowin more detail in connection to FIG. 4. The exposure to x-rays causeseach material to fluoresce x-rays at various energy levels, producing anxrf spectrum. In step 57, this xrf spectrum is detected by an x-raydetector.

Next, in step 59, for each piece of material, the material is classifiedbased on the xrf that was detected, as discussed in more detail below inconnection to FIG. 3.

Next, in step 61 of FIG. 2B, an air jet corresponding to theclassification of the piece is activated. Between the time at which thepiece of material was irradiated and the time at which the air jet isactivated, the piece of material has moved from the detection chamber toa point downstream from the detection chamber, at the rate of conveyingof the belt. In an embodiment, the activation of the air jet is timedsuch that as the piece passes the air jet mapped to the classificationof the piece, the air jet is activated and the piece of material isejected from the conveyor belt.

In an alternative embodiment, the activation of air jet is timed by arespective position detector that detects when a piece of material ispassing before the air jet and sends a signal to enable the activationof the jet. In step 63, the sorting bin corresponding to the air jetthat was activated receives the ejected piece of material.

FIG. 3 is a diagram illustrating an illustrative embodiment of the x-raydetection chamber 7. A power supply 45 supplies power to an x-ray source47. For example, the power supply may be a Spellman RMP 300 powersupply, and the x-ray source 47 is an x-ray tube such as, for example, awater-cooled Varian OEG-50 x-ray tube. Such an x-ray tube and powersupply combination is capable of operating at up to 300 watts at 30 kv.In an illustrative embodiment, the x-ray tube is operated at 13-17 kv atlevels in the range of 1-10 watts.

The intensity of x-rays is proportional to the rate at which x-rays aretransmitted. Although commercially available x-ray sources usingradioactive isotopes, for example Cd¹²⁹, Am²⁴¹, and Co⁵⁷, and Fe⁵⁵ maybe used as the x-ray source 47, as is common in material sorting systemsthat detect xrf, such isotope-based sources do not produce x-rays at theintensity that can be produced by an x-ray tube. The number of x-raysfluoresced 26 from a piece of material 25 irradiated with x-rays 24 is afunction of the intensity and energy levels of the irradiating x-rays24. Thus, when an x-ray source 47 is used that produces less intensex-rays 24, less x-rays 26 are fluoresced from the piece of material 25.Consequently, fluoresced x-rays 26 must be detected from the piece ofmaterial 25 for a longer period of time so that an xrf spectrum with astrong enough image, i.e. a recognizable spectral pattern, may bedetermined

Therefore, to increase the speed of detection and classification, anx-ray tube may be used as the x-ray source 47. An x-ray tube is capableof producing x-rays several orders of magnitude more intense than anycommercially available isotope-based x-ray sources. This intensity isparticularly important when the piece of material 25 is relativelysmall, when the x-ray source 47 is a relatively long distance away fromthe piece of material 25, or when the piece of material 25 is arelatively long distance away from the detector 27, the reasons forwhich are discussed in more detail below. Further, an x-ray tube has theadded advantage of being capable of being turned off when not in use, incontrast to a radioactive isotope. As used herein, the term “highintensity” when used to describe x-rays means x-rays of an intensity atleast an order of magnitude more intense than the x-rays produced from atypical, commercially-available isotope-based x-ray source.

Using an x-ray tube, or another comparable high intensity radiationsource, as the x-ray source 47, however, causes massive amounts ofx-rays to be present in the x-ray chamber 7, orders of magnitude morethan would be present if an isotope-based source were used. The presenceof this amount of x-rays causes problems with the detection of x-rays bythe x-ray detector 27 and the determination of an accurate xrf spectrum.Therefore, the irradiation and detection of the x-rays must beconditioned as described in more detail below.

In an illustrative embodiment, the x-ray source 47 is collimated by acollimator 49, having an aperture which is aimed at a detection areawhere a particular piece of material 25 is to be irradiated. In anillustrative embodiment, the detection area is approximately a circlewith a diameter of about 2.5″. As used herein, a “collimator” is adevice having an aperture which limits the transmission of x-rays of anx-ray stream such that the x-rays move in the same, or nearly the same,direction.

An x-ray detector 27 detects the x-rays fluoresced from the piece ofmaterial 25, and sends a signal representing the detected x-rays alongthe signal carrier 8 to the xrf processing module 9. In an illustrativeembodiment, the x-ray detector 27 is collimated by a collimator 29. Anaperture of collimator 29 aims x-ray detector 27 at the piece ofmaterial 25 during detection such that detector 27 directly receivesfluoresced x-rays 26 from piece of material 25 while extraneous x-raysincluding x-rays 24 irradiated from x-ray source 47 and incidentalx-rays from other objects within the detection chamber 7 are inhibitedby collimator 29 from reaching detector 27, thereby reducing detectionof these extraneous x-rays by detector 27. These direct and incidentalx-rays are referred to herein as background noise. Background noiseincludes x-rays fluoresced or reflected from objects in the chamber 7other than the piece of material 25, including: the interior surfaces ofthe chamber 7 itself; items used to fasten together sections of thechamber 7 itself; the conveyor belt 5; or any other objects present inthe chamber. Such background noise may be caused by the irradiatingx-rays 24 and fluoresced x-rays 26 impacting other objects in thechamber 27 and causing secondary fluorescence.

In an illustrative embodiment in which a high intensity x-ray source 47is used, the high intensity x-rays 24 bombarding the piece of material25 cause the piece of material 25 to fluoresce x-rays 26 of highintensity. Because of these high intensity x-rays, it is necessary touse an x-ray detector 27 capable of handling the high intensity xrfwithout flooding. An example of an x-ray detector capable of handlingthe high intensity fluorescence x-rays is the Amptek XR-100T with Si-PINdiode detector and beryllium window to admit low energy x-rays. Theenergy resolution of the Amptek detector is 250 ev or 0.25 Key. However,improved x-ray detectors are currently being developed which are capableof even smaller (more precise) energy resolution. Thus, the choice ofresolution of an xrf spectrum is a function of the resolution desiredand the resolution capability of the x-ray detector 27.

In an illustrative embodiment, the x-ray detector 27 is highlysensitive, and when too many x-rays impact the x-ray detector 27, it maybecome flooded with fluoresced x-rays. Such flooding may cause the x-raydetector 27 to malfunction or reduce the accuracy of the determined xrfspectrum. When too many x-rays impact the x-ray detector 27, theaccuracy of the spectrum determination may be reduced because not all ofthe fluoresced x-rays 26 will be detected. Thus, in an illustrativeembodiment, accurate classification is best achieved by generatingx-rays 24 at an intensity that will not cause the x-ray detector 27 tobe flooded by irradiation. Thus, the x-ray 47 source may be operated atpower levels to produce relatively low intensity radiation such as, forexample, at 13.5 V and 0.03 mA, giving an x-ray power output of only 0.4watts.

The x-rays 24 emitted by the x-ray source 47 may be filtered by an x-rayfilter. Such filtering is beneficial when an x-ray source 47 that has abroadband energy output (emits x-rays of a wide range of energy levels)for example, an x-ray tube, is used. Such broadband energy includesunneeded x-rays that produce increased background noise in the x-raydetection chamber 7. Unneeded irradiated x-rays are irradiated x-rays ofan energy level insufficient to cause the piece of material 25 tofluoresce x-rays within an energy range of the determined xrf spectrum.For example, if the determined x-ray spectrum is programmed to have anenergy range between 5 key and 30 key, then only fluoresced x-rays 26within this range are relevant for classification of the piece 25.Generally, to cause the fluorescence of an x-ray at a given energylevel, an impacting irradiated x-ray must have an energy level equal toor greater than the given energy level. Thus, to cause the fluorescenceof an x-ray of between 5 key and 30 key, an impacting irradiated x-raymust have an energy level of at least 5 key. Thus, any x-rays irradiated24 from the x-ray source 47 that are less than approximately 5 key areunneeded. The term extraneous x-rays, as used herein, includes bothbackground noise and unneeded irradiated x-rays. The unneeded x-rays maycause additional background noise, and the unneeded x-rays alone or incombination with the background noise may flood the x-ray detector 27.Thus, an x-ray filter may be used to reduce the number of unneededx-rays impacting the piece of material 25 or impacting the x-raydetector 27.

As discussed above, in an illustrative embodiment using a high energyx-ray source, such as an x-ray tube, a high amount of background noiseis generated. Although typically a conveyor belt made of some sort ofrubber material is used in sorting systems, the intensity of the x-rays24 generated from the x-ray source 47 cause even elements present in arubber belt to emit x-rays. Therefore, in an illustrative embodiment,the belt preferably is made of a material that will not fluoresce x-raysat energy levels that fall within the range of the energy spectrum beingdetected, thereby interfering with the energy spectrum. The energy levelof the fluoresced x-rays depends on the energy levels at which theelements present in the piece of material 25 fluoresce. The energy levelat which an element fluoresces is proportional to its atomic number. Forexample, elements of low atomic numbers fluoresce x-rays at lower energylevels. Thus, the material for the conveyor belt may be chosen such thatthe belt comprises elements of certain atomic numbers that do notfluoresce x-rays within a certain energy range. For example, PVCcontains chloride which fluoresces at a low energy level, and therefore,when an xrf spectrum with a relatively high energy range is beingdetermined, PVC may be a good choice as a material for the conveyorbelt.

For the same reasons as discussed above with respect to the conveyorbelt 5, the x-ray detection chamber 7, or at least the interior surfaceof the x-ray detection chamber 7, may be made or lined with a materialthat fluoresces at particular energy levels such as, for example, PVC.Further, the collimator 49 for the x-ray source 47 may be made of amaterial that fluoresces at particular energy levels such as, forexample, PVC.

X-ray chambers, such as x-ray chamber 7, are typically shielded with alayer of lead along the interior surface to absorb the x-rays and thusprotect persons in the vicinity of the x-ray chamber. In a high speedmaterial sorter, however, when a high intensity x-ray source such as anx-ray tube is used, if the intensity is high enough, the lead itselfbegins to fluoresce x-rays at a level that may interfere with thedetector. If there are enough x-rays fluoresced from the lead, the x-raydetector may be flooded, and the accuracy of the determined xrf spectrummay be reduced. To reduce the probability of flooding the x-ray detector27, the x-ray chamber 7 may be lined with a material, for example, PVC,that fluoresces x-rays at lower energy levels at which the x-rays have ahigher probability of being absorbed by air.

Besides reducing the accuracy of the xrf spectrum by flooding, the xrfspectrum may be further compromised by incorrectly indicating that thepiece of material 25 contains lead, or a different amount of lead thanis correct, which may lead to incorrect classification. Such a situationwould arise if lead fluoresced within the energy spectrum beingdetermined. In such a situation, to avoid loss of x-ray fluorescencespectrum accuracy, lead should not be used to line the interior surfaceof the x-ray chamber.

In an illustrative embodiment, the xrf detected by the x-ray detector 27is collimated by a collimator 29. The collimator 29 limits the effectsof extraneous x-rays being received by the x-ray detector 27, by aimingthe detector 27 at the detection area where the x-rays 26 are fluorescedby the piece of material 25. In an illustrative embodiment, thiscollimator 29 is made of a material or materials that fluoresces atparticular energy levels such as, for example, PVC, for the same reasonsdiscussed above with respect to collimator 49, x-ray chamber 7, andconveyor belt 5.

Thus, when using an x-ray source 27 of high intensity, such as an x-raytube, the irradiation and detection of the x-rays may be conditioned inorder to accurately detect the xrf of a piece of material and accuratelyclassify the piece. Conditioning the irradiated x-rays may includecollimating the x-ray source 49 and filtering the x-rays 24 produced bythe x-ray source 47. Conditioning the detection of x-rays may includecollimating the x-ray detector 27, and using materials that fluoresce atlow energy levels for many of the components proximate to detection areasuch as, for example, the conveyor belt 5 and the x-ray chamber 7.

For high speed sorting of materials using an x-ray source that producesx-rays of high intensity, collection intervals for collecting x-rayspectra may range lower than 10 ms (ms). Longer intervals such as, forexample, 5 seconds, may be used to collect reference spectra that arestored for comparison against detected spectra. Generally, the long-timespectra are less noisy than the shorter duration samples since randomvariations of the fluorescing and detection of x-rays thus of the outputof the detector 27, tend to cancel over time.

In the illustrative embodiment of FIG. 3, the x-ray source 47 is locatedabove the detection area. In alternative illustrative embodiments, thex-ray source may be located to the side of detection area, or beneaththe belt. Locating the x-ray source beneath the detection area, however,requires maintaining a surface, perhaps a portion of the belt, throughwhich the x-rays must penetrate to irradiate the piece of material 25.In such an illustrative embodiment, the belt may have a meshconfiguration, or may have apertures through which x-rays may passthrough the belt impeded mainly by the x-ray absorption of air. Further,the composition of the belt may be such that the belt is largelytransparent to the transmission of x-rays. Although locating the x-raysource beneath the detection area requires maintaining a surface, suchan arrangement does place the x-ray detector closer to materials,regardless of the size of the materials. This arrangement therefore mayincrease the number of irradiating x-rays that impact the piece ofmaterials, resulting in an increased number of x-rays fluoresced and anincreased number of detected x-rays.

FIG. 4 is a diagram illustrating an illustrative embodiment of the xrfprocessing module 9. The x-ray detector 27 sends a signal that carriesthe xrf detected from the piece of material 25 along a signal carrier 8.The xrf signal is amplified by amplifier 31 to produce an amplified xrfsignal transmitted on signal carrier 10 which is received by a spectrumacquisition module 33. In an illustrative embodiment, the amplifier 31is an A250 preamplifier that conditions the signal to produce theamplified xrf signal on signal carrier 10.

FIG. 5 is a data flow diagram illustrating an illustrative embodiment ofthe function of the spectrum acquisition module 33. The spectrumacquisition module 33 receives the amplified xrf signal and converts theamplified xrf signal into a discrete energy histogram spectrum 34. In anillustrative embodiment, the spectrum acquisition module comprises anAmptech MCA 5000 acquisition card and software programmed to operate thecard at a real-time rate. The Amptech MCA card has 2048 channels fordispersing x-rays into a discrete energy spectrum with 2048 energylevels. In this illustrative embodiment, for each collection interval,the energy count for each energy level may be stored in a separatecollection register. A processor of the xrf processing module 9 may thenread each collection register to determine the number of counts for eachenergy level during the collection interval, and build the energyhistogram. The processor interfaces to the Amptech card by executing I/Oreads and writes across a bus such as, for example, an ISA bus. In thisillustrative embodiment, the general procedure for obtaining a spectrumis: load timer registers, issue start collection command, wait for donestatus, and copy the collection registers to a computer-readable memory.

The sorting application 35, also referred to herein as theclassification module, executes a sorting algorithm that classifies thepiece of material 25 by recognizing the spectral pattern of the xrfspectrum of the piece. FIG. 6 is a flow chart showing an illustrativeembodiment of step 59 of FIG. 2A for classifying the piece based on thexrf spectrum of the material. In step 59, each energy count of the xrfspectrum is normalized such that each energy count may be considered adimensional component of an xrf unit vector. Accordingly, each energycount is reduced by an amount equal to:

$\frac{1}{\sqrt{\left( {a^{2} + b^{2} + {c^{2}\mspace{14mu} \ldots \mspace{14mu} n^{2}}} \right)}}$

where a, b, c and n are energy counts at various energy levels.

The energy range of the xrf spectrum determined by the spectrumacquisition module 33, the number of energy levels of the determined xrfspectrum, and the resolution of the determined xrf spectrum are allprogrammable. These parameters may be chosen depending on the sort to beperformed. If a large range of materials are being sorted, the energyrange may be large and the number of energy levels high. If pieces ofmaterials are to be sorted have relatively similar compositions, thenthe resolution may be fine, so as to distinguish between the spectralpatterns. For example, when pieces of metal are to be sorted intoaluminum, brass, chrome plated zinc, copper, stainless steel, and zinc,the spectrum acquisition module 33 may be programmed to detect and countx-rays at 256 energy levels ranging from 0 key to 25.6 key with 0.1 keyresolution.

Next, in step 63, the vector dot products are computed between thenormalized detected xrf spectrum and the normalized xrf spectra of anystored reference materials. Prior to starting the sorting process, a setof reference samples is collected and the xrf spectra of these samplesdetermined and stored, for example, in a non-volatile storage medium 41.In an illustrative embodiment, for reference spectra, the x-ray spectrumof each reference material is collected over an interval of 5 seconds.

To compute the dot product, if the detected normalized reference spectrahas normalized energy counts of a₁, a₂, . . . a₂₅₆, and the normalizedxrf spectrum of a reference material has normalized energy counts of b₁,b₂, . . . b₂₅₆, then the vector dot product between these two spectrawould be a₁×b₁+a₂×b₂+ . . . a₂₅₆×b₂₅₆. Because all the spectra have beennormalized to a unit vector, the dot products between two identicalspectra would produce the value 1, where the results of all dot productsshould be between the 1 and 0. A dot product of 0 results if for everyenergy level of the detected spectrum for which at least a single countis detected, the reference spectrum does not have a single energy count,or vice versa.

A user interface 37 provides functions to sample, view, and compareindividual spectrums to prepare the reference material set and todesignate which references will be “active” and read into fastervolatile memory for use during execution of the sorting algorithm. Thus,the xrf processing module computes a vector dot product between thenormalized xrf of the detected material and the normalized xrf spectrumof each of the active reference materials.

Next, in step 65, it is determined whether any of the computed vectordot products reach a minimum threshold value. In an illustrativeembodiment, there is a single minimum threshold value that must beachieved for any of the reference spectra. In an alternativeillustrative embodiment, each reference spectrum has an individualminimum threshold value that the dot product calculated for thereference spectrum must equal or exceed. Having an individual thresholdvalue for each reference spectrum adds additional flexibility indistinguishing between similar spectral patterns, as is discussed inmore detail below.

The threshold values for reference spectra are programmable by a systemuser. The closer the spectral patterns of two reference spectra, thehigher the threshold value for these reference spectra should beprogrammed in order to positively distinguish the two spectra. Forexample, if a user is only interested in distinguishing between a firstspectral pattern that has several peaks at certain energy levels, and asecond spectral pattern that has energy peaks at certain other energylevels, then the user may program the threshold value for these tworeference spectra to be relatively low to distinguish between the twospectral patterns (although the threshold value should be high enough todistinguish the two reference spectra from other reference spectra).Conversely, if two spectral patterns have energy peaks that share commonenergy levels and where, for these energy levels, the normalized countvalue for each spectra is close to the other, then the threshold valueshould be set relatively high. The value of the threshold must be sethigh enough so that the spectral pattern of a detected piece of materialmust be very close to matching one of the two reference spectra for aclassification to be made. This high threshold ensures correctrecognition of a spectral pattern.

If it is determined in step 65 that at least one vector dot productreaches a minimum threshold value, then at step 67 it is determinedwhich computer dot product value has the highest value. The dot productof the highest value indicates the reference spectra closest to thedetected spectra. In an alternative illustrative embodiment, where eachspectrum has an individual threshold value, it is determined for whichof the reference spectra the highest dot product was calculated forwhich the minimum threshold for the reference material was reached.

Consequently, in step 69, the classification corresponding to the storedspectrum that produced the highest dot product and equals or exceeds aminimum threshold is determined. Such a classification may be encoded ona classification signal. In an alternative illustrative embodiment ofstep 69, the classification corresponding to the stored spectrum whosedot product exceeds the spectrum's threshold value by the greatestpercentage is selected. For example, assume spectra A has a threshold of0.4 and spectra B has a threshold of 0.6. In addition, assume a dotproduct of 0.7 is calculated for spectra A and a dot product of 0.8 iscalculated for spectra B. The classification corresponding to Spectra Awould be selected even though Spectra B′s dot product is higher becauseSpectra A's dot product is 75% over its threshold, while Spectra B's dotproduct is only 33% over its threshold.

Classifying a piece of material by comparing the spectral shape orspectral pattern of the xrf of a spectrum contrasts to known methods ofanalyzing only energy counts of select peak energy levels. Such knownmethods merely determine whether the number of counts for select energylevel exceeds a threshold value, or compare the counts of the selectenergy levels to the counts from corresponding select peak energy levelsof a reference spectrum. Each selected energy level is typicallyindicative of a particular element present in the piece of material. Insome known systems, the selected peaks are normalized, such that theresulting normalized peaks reflect the proportion of each element in thepiece of material. Typically, known methods require that the xrf of apiece of material is detected over a relatively long period of time suchas, for example, a second or more. Detecting over such a long periodensures that the selected peaks accurately reflect the proportion ofeach element.

The sorting algorithm described herein is a faster and more flexiblemethod of classifying a piece of material than those known methodsdescribed above. First, comparing the spectral pattern or image of thedetected xrf spectrum to the spectral pattern or image of storedreference spectra permits an accurate classification to be made evenwhen only a faint or weak image of the xrf spectrum of a piece ofmaterial is known (i.e. the detected spectral pattern takes the generalshape of the spectral pattern of a reference spectrum). Therefore,precise composition of a piece of material need not actually bedetermined (although it may be). Such a faint image results when arelatively limited number of x-rays or counts have been detected. Lesscounts result from shorter detection times. Thus, recognition of a faintimage permits a piece of material to be classified in shorter detectiontimes, substantially less than one second, possibly shorter than 10 ms.

Second, the sorting algorithm described herein permits a materialsorting system to have greater flexibility in sorting materials than doknown sorting algorithms allow. A user may select a random sample to useas a reference sample, establish the random sample as a referencespectra by detecting the xrf from the random sample for a relativelylong interval of time, for example 5 seconds, in order to eliminate anyrandom variations in the detected xrf, and store the xrf spectrumdetermined from the detected x-rays. The xrf spectrum of the randomsample can then serve as a reference spectra by which other pieces ofmaterial can be detected and compared against to determine whether thedetermined xrf spectra matches the reference spectra created from therandom sample. A user would not have to program the processing module toanalyze certain peak energy levels of the new reference xrf spectrum andfuture determined xrf spectra. In contrast, the sorting algorithm wouldcompare the spectral patterns without regard for peak energy levels.Known sorting methods require that sorting parameters be reconfigured toanalyze the peak energy levels of the reference xrf spectra anddetermined xrf spectra.

FIGS. 7A and 7B are each a diagram illustrating an illustrativeembodiment of using energy histograms to represent an x-ray fluorescencespectrum. Energy histogram 70 represents the comparison between the xrfspectral pattern of an unknown piece of material B08 and the xrfspectral pattern of chromeplate. Energy histogram 72 represents thecomparison between the xrf spectrum of B08 and the xrf spectrum of brass360. For illustrative purposes, the xrf spectral pattern of B08 isrepresented as a discrete energy counts, while the xrf spectral patternsof reference materials chromeplate and brass 360 are represented as acurve. For example, in energy histogram 70, 74 represents a discreteenergy count of B08.

The reference spectral curves 73 and 75 illustrate the fact thesespectral patterns were constructed from xrf collected over asignificantly longer collection interval than the detected pattern.Thus, the reference curves 73 and 75 are a more complete image of theirrespective xrf spectra than the faint image presented by the energycounts of B08.

The energy histograms 70 and 72 indicate that the unknown material B08is a piece of brass, the xrf of which was collected over a relativelybrief interval of time such as, for example, 50 ms. The referencematerials chromeplate and brass 360, on the other hand, are collectedover a relatively long period of time, for example 5 seconds. As can beseen from the energy count histogram 72, from the energy histogramitself and from the information panel 78, the brass reference, brass360, is a very close match to the brass sample B08. The lower right boxof the information panel 78 indicates that the vector dot productproduced from the comparison of these two spectral patterns is 0.961. Onthe other hand, as shown by energy histogram 70, the chrome platereference is not a very close match for the brass sample B08. This isindicated visually in the energy count histogram itself and also by thevector dot product of 0.292 indicated in the lower right hand box of theinformation panel 76.

In FIGS. 7A and 7B, energy peaks of various elements present in thematerials are identified. For example, nickel (Ni) has an energy peak at7.48 keV. As discussed above, known systems are typically limited toanalyzing only the energy peaks, such as those shown in the energyhistograms of FIGS. 7A and 7B. These energy peaks are highly indicative,however, of the composition of the reference material or the samplematerial. The partial dot product calculated between two energy peaks,comprising the multiplication of the normalized energy counts from eachspectra at these energy peaks, has a greater impact on the overallvector dot product than the partial dot products produced by multiplyinglower energy counts. Thus, the sorting algorithm described herein,although considering a large range of energy levels, still statisticallygives more weight to the peak energy levels characteristic of theelemental materials included in a material.

Returning to FIG. 4, the sorting application 35 accesses spectral datafrom the spectrum acquisition module 33 and uses the data to execute thesorting algorithm described above to determine which of the air jets13-17 to activate in accordance with the classification of the piece ofmaterial. The sorting application 35 may also store data in anon-volatile computer readable medium 41 such as, for example, adatabase. The database may be implemented with Microsoft Access, Cybase,Oracle, or other suitable commercial database systems. Such data mayinclude xrf spectra received from the spectrum acquisition module 33,sorting parameters, and the results of comparisons, e.g., dot products,between detected xrf spectra and reference xrf spectra. Once the data isstored in a database, such data may be analyzed using known databaseanalysis tools, such as a query language such as, for example, MicrosoftSQL.

The sorting application 35 also sends data to and receives commands froma user interface 37 that may provide a visual display to a system useron a video display device such as a monitor 43. The details of thegraphical display produced by the user interface 37 is described in moredetail below in connection with FIG. 8.

In an illustrative embodiment, the sorting application 35 executes at areal time rate, the functionality required by the sorting algorithmexecuted by the sorting application 35 being separate from the userinterface 37. In an illustrative embodiment, the xrf processing module 9runs an operating system on a computer such as, for example, WindowsNT®,a general-purpose operating system. Other known commercial operatingsystems suitable to implement the sorting application 35 and the userinterface 37 may be used. In an illustrative embodiment, the delays intiming uncertainties introduced by WindowsNT affect only the userinterface and not the sorting algorithm. In an illustrative embodiment,all software system components are written for WindowsNT 4.0 usingMicrosoft Visual C++ and Imagination Systems' HyperKernel real-timeextension. The Sommer application discloses source code that may be usedto implement the sorting application 35.

In an illustrative embodiment, the sorting application 35 executes on areal-time operating system.

In an alternative illustrative embodiment, the sorting application 35 isa real-time module that executes “underneath” the operating system, andcontains the entire sorting algorithm as well as any necessarysorting-hardware references. A real-time extension such as, for example,the Imagination System's HyperKernel, of the Windows NT operating systemmay provide guaranteed real-time control that is isolated from thenon-deterministic delays introduced by a general-purpose task scheduler.HyperKernel library functions may be used for unrestricted access to anejector air valve controller 42, and to registers of external hardware,such as a hardware illustrative embodiment of the spectrum acquisitionmodule 33.

The sorting algorithm described herein requires that spectra be capturedand processed at a precise rate with millisecond accuracy. The speed andprecision of this execution are functions of the actual time forexecuting the algorithm code, and the scheduling of the timed events ina multi-tasking environment. If the time required to execute thealgorithm were to exceed an inter sample period, then an auxiliaryembedded processor would be required. If a host computer has sufficientbandwidth to execute the algorithm within the required time, theoperating system must also ensure that the algorithm's tasks are notdelayed by tasks from other application or system service processes.

The second requirement is often the most difficult to satisfy. Although,contemporary PC hardware provides sufficient processing power to executeall but the highest data-rate or most calculation-intensive algorithms,general purpose multi-tasking operating systems, like Windows NT, cannotguarantee real-time millisecond-precision service for the algorithm'scode. In an illustrative embodiment, a separate embedded processor boardis used to guarantee real-time execution of the sorting algorithm, evenwhen the host CPU may have adequate bandwidth. In another illustrativeembodiment, a real-time extension to WindowsNT is implemented to provideguaranteed time-slices to the sorting algorithm. The real-time extensionallows the algorithm to be implemented as a multi-threaded applicationsystem with guaranteed sub-millisecond real-time precision, so that theoperating system (and its extension) scheduler satisfies the secondrequirement. The result is a xrf processing module 9 that can supportthe sorting algorithm without the cost of an additional embeddedprocessor board.

The sorting algorithm executed by the sorting application 35 requiresthat xrf be detected, the spectral pattern determined, and the piece beof material be classified over short time intervals such as, forexample, less than a second. The processing speed of most of today'scommercial PCs permits execution of the sorting algorithm in less than 1ms. Even a computer system implementing a 166 megahertz Pentiumprocessor can execute the sorting algorithm in less than 2 ms if run asa single non-interrupted thread of execution. The x-ray detector 27,however, requires 10 ms to 50 ms to acquire the spectrum, depending onthe intensity of the x-ray source 47, the respective distances betweenthe x-ray detector 27, the x-ray source 47, and the piece of material 25during detection, the composition of objects within the x-ray chamber,the conditioning of the x-ray detection and irradiation, the duration ofthe detection, and various parameters of the x-ray detector 27. Thus,the speed of the entire process is essentially limited by theacquisition time for the spectra.

The amount of xrf detected from a piece of material depends on thedetection time, which depends on the size of the piece of material andthe time the material spends in the detection area. Systems that rely onthe number of energy counts, as opposed to the proportional relationshipbetween energy counts must know the size of the piece of material andthe time spent under the x-ray detection device by the material. Thehigh speed material sorting system and process described herein may beused to sort materials of various sizes because the sorting algorithmdepends on the proportions of the energy counts as opposed to the volumeof the energy counts. Further, the sorting algorithm can classify apiece of material from the recognition of a faint image of the spectralpattern of the piece.

Further, because x-rays are detected and an xrf spectrum is determinedat a much faster rate, cumulatively, and because less x-rays are neededto classify a piece of material, pieces of materials as small as ¼ inchmay be classified at rates fast enough to make the sorting and recyclingof such pieces economically valuable. Size as used herein to describethe size of a piece of material means the largest diameter of the pieceof material in any dimension.

A problem with known material sorting systems, where pieces of materialsare conveyed along a conveyor belt, is that it is difficult to detectspecific elements that fluoresce at low energy levels because the x-raysfrom these elements are so weak that the x-rays are absorbed by airbefore reaching a detector. For example, aluminum is difficult to detectbecause it fluoresces at energy levels below 2 key, and these x-rays aremostly absorbed by air before reaching an x-ray detector. Although theproceeding example uses aluminum for illustrative purposes, the exampleapplies analogously to other elements that fluoresce at low energylevels. One solution is to put the x-ray detector closer to the piece ofmaterial that includes the aluminum. However, when conveying pieces ofmaterials of variable size along a conveyor belt, the x-ray detectormust be kept at a distance sufficient to accommodate the largestpossible size of a piece. Thus, small pieces may be further away fromthe x-ray detector than larger ones.

In an illustrative embodiment of a high speed sorting of materials, apiece of material comprising aluminum, or any element that fluoresces atlow energy levels, may be classified by recognizing the spectral patternof the material as a whole. For example, aluminum may be classified bythe spectral pattern of its alloys by storing the spectral pattern ofaluminum alloys as reference spectra, and mapping an air jet to eachreference spectra. In an illustrative embodiment, if it is desired tosort all aluminum alloys into a common bin, multiple air jets may bemapped to a common sorting bin. The high speed material sorting processas described herein may be executed, and pieces of aluminum alloy may berecognized and sorted in accordance with the sorting algorithm.

In an illustrative embodiment of a high speed material sorting system,multiple sorting systems may be used in parallel, each sorting systemoptimized for a particular classifications of materials or particularpiece sizes. For example: a first system may sort pieces of materialhaving a size from approximately ¼ inch to approximately ⅝ inch; asecond system may sort pieces having a size from approximately ⅝ inch to4 inches; and a third system may sort pieces between 4 inches and 12inches. Prior to sorting, a feedstock of materials could be pre-sortedinto feedstocks, one for each size category. For each size-specificsystem, various parameters could be optimized for the size of thematerials it sorts. Parameters that may be adjusted include: the widthand length of the belt; the width and height of the chamber; the speedof the belt; the distance between the x-ray source and the detectionarea, the distance between the x-ray detector and the detection area;the power of the x-ray source resulting in the intensity of theirradiated x-rays; the resolution of the determined spectra; thereference spectra; the number of reference spectra; the threshold valuefor each spectra; the number of sorting bins; the mapping of referencespectra to sorting bins, etc.

In an illustrative embodiment of a high speed materials sorting system,multiple x-ray detectors may be used. Such x-ray detectors may be all beaimed at the same detection area, or may be aimed at different detectionareas. The x-rays detected by the multiple detectors may all be causedby a common x-ray source or multiple x-ray sources, where the x-raydetectors may be placed in series along the path of the conveyor belt.Using multiple x-ray detectors allows for the gathering of more xrf toproduce a more accurate spectral pattern of a piece of material, thusreducing the effects of random variations inherent with detectingx-rays.

In an illustrative embodiment of a high speed materials sorting system,materials may be sorted using a type of binary sort. For example, asopposed to the air jets 13-17 ejecting pieces of materials into sortingbins 18-22, the air jets can be used to eject the piece of materialsonto additional conveyor belts that lead to additional sorting.

FIG. 9 is a block diagram illustrating an example illustrativeembodiment of a binary sort. In a first stage of the binary sort,materials may be sorted into metals 120 and non-metals 122 by a materialsorting system such as, for example, the high speed material sortingsystem 1 of FIG. 1. The system may eject metals onto a first belt forconveying metals into a material sorting system for sorting metals, andeject non-metals onto a second belt for conveying non-metals into amaterial sorting system for sorting non-metals. To implement this firstsort, the reference spectra of each sorting system and their respectivethreshold values may be selected such that the each sorting system isdesigned to differentiate between metals and non-metals. Selecting aproper threshold for a particular sort is described above with respectto the sorting algorithm.

In another stage of the binary sort, non-metals 122 may be sorted intoplastics 124 and ceramics 126, while metals 120 may be sorted into redmetals 130 and other metals 128. The red metals 130 may then beseparated into copper 134 and brass 132. Each sort may be performedanalogously to the process described above with respect to the firststage of the binary sort.

FIG. 8 is a screen capture illustrating an illustrative embodiment ofgraphical display generated by a user interface 37. In an illustrativeembodiment, the user interface 37 is a graphical application writtenwith standard Microsoft tools and libraries and executes strictly in NTuser space. Other known commercial tools and libraries may be used. Theuser interface functions for screen management, keyboard or mouse input,and file I/O may be supported by the standard WIN 32 libraries. Thisgraphical application may run simultaneously with other applications,and may be executed (and task-swapped) by an NT task scheduler.

Although not shown in FIG. 4, an interface may be provided between theuser interface 37 and the sorting application 35. This interface passescommands between the user interface 37 and the sorting application 35,and the sorting algorithm results are passed back for display by theuser interface 37. A HyperKernel extension library may manage ashared-memory region that is used to exchange data between the userinterface 37 (and user, or virtual memory space) and the real-time code(in kernel, or physical memory space) of the sorting application 35.

In this illustrative embodiment, the graphical display 80 includesbuttons at the top and left of the screen that are used for programcontrol, setting parameters, and database management. Reference materialbutton 94 allows a system user to set parameters for referencematerials. Data acquisition button 96 allows a user to set parametersfor data acquisition. The ejector control button 98 allows a user to setparameters for controlling ejection via the air jets. Results monitorbutton 100 allows a system user to set parameters for monitoring theresults of the sorting algorithm. Start button 102 permits a system userto start the sorting algorithm, while stop button 104 allows the systemuser to stop the sort algorithm. Check box 106 allows a user to enableor disable the ejectors. Configuration button 108 permits a system userto save the current configuration. Save dot product button 110 permits asystem user to save the results of a dot product between the xrfspectral pattern of a detected material and the xrf spectral pattern ofa reference material.

The histogram chart 82 displays a scrolling time histogram of dotproduct values taken with each reference spectra as a sample movesthrough the detection chamber 7. The numeric tables 86, 88, 90 on theright of the screen show dot product values and sorting thresholdsettings. The instant dot products table 90 shows the dot productsbetween a detected material and a reference material at a point in timeindicated by cursor 114, the cursor 114 being adjustable by a systemuser. The average dot product table 88 displays the average dot productacross the time interval displayed in the histogram chart 82. Thethreshold table 86 indicates the threshold value for the correspondingreference material of the reference material column 116.

The ejection destination chart 84 identifies the air jet/sorting bincorresponding to the classification of the piece of material determinedby the sorting algorithm. For example, in the histogram chart 82, thedot products of the highest value at the instant indicated by the cursor114 is that of Cu 38 (copper), which, as indicated by the instant dotproduct table, has a dot product of 0.903. In accordance with thisdetermination, the ejector designation chart shows that the Cu/brass(copper/brass) ejector has been designated for the piece of material.

The high-speed metal sorting system and method disclosed herein allowsfor hand shearing to be replaced by automated size reduction and sortingtechniques such as shredding, grinding, crushing, air classification,eddy-current separation, magnetic separation, and screening. High-valuemetals, or other materials, can be liberated from non-metals or fromlower value metals or materials to which they are adjoined. Onceliberated and grouped by size, the particles may be singulated (particleby particle with spaces between particles) and fed onto conveyor belt 5.

The xrf processing module 9 may be implemented with a typical computersystem. The invention is not limited to any specific computer describedherein. Many other different machines may be used to implement the xrfprocessing module 9. Such a suitable computer system includes aprocessing unit which performs a variety of functions and a mannerwell-known in the art in response to instructions provided from anapplication program. The processing unit functions according to aprogram known as the operating system, of which many types are known inthe art. The steps of an application program are typically provided inrandom access memory (RAM) in machine-readable form because programs aretypically stored on a non-volatile memory, such as a hard disk or floppydisk. After a user selects an application program, it is loaded from thehard disk to the RAM, and the processing unit proceeds through thesequence of instructions of the application program.

The computer system also includes a user input/output (I/O) interface.The user interface typically includes a display apparatus (not shown),such as a cathode-ray-tube (CRT) display in an input device (not shown),such as a keyboard or mouse. A variety of other known input and outputdevices may be used, such as speech generation and recognition units,audio output devices, etc.

The computer system also includes a video and audio data I/O subsystem.Such a subsystem is well-known in the art and the present invention isnot limited to the specific subsystem described herein. The audioportion of the subsystem includes an analog-to-digital (A/D) converter(not shown), which receives analog audio information and converts it todigital information. The digital information may be compressed usingknown compression systems, for storage on the hard disk to use atanother time. A typical video portion of subsystem includes a videoimage compressor/decompressor (not shown) of which many are known in theart. Such compressor/decompressors convert analog video information intocompressed digital information. The compressed digital information maybe stored on hard disk for use at a later time.

One or more output devices may be connected to the computer systemimplementing the xrf processing module. Example output devices include acathode ray tube (CRT) display, liquid crystal displays (LCD) and othervideo output devices, printers, communication devices such as a modem,storage devices such as disk or tape, and audio output. One or moreinput devices may be connected to the computer system. Example inputdevices include a keyboard, keypad, track ball, mouse, pen and tablet,communication device, and data input devices such as audio and videocapture devices and sensors. The computer system is not limited to theparticular input or output devices used in combination with the computersystem or to those described herein.

The xrf processing module 9 may be implemented on a general purposecomputer system which is programmable using a computer programminglanguage, such as “C++,” JAVA or other language, such as a scriptinglanguage or even assembly language. The computer system may also bespecially programmed, special purpose hardware. In a general purposecomputer system, the processor is typically a commercially availableprocessor, such as the series x86 and Pentium processors, available fromIntel, similar devices from AMD and Cyrix, the 680X0 seriesmicroprocessors available from Motorola, and the PowerPC microprocessorfrom IBM. Many other processors are available. Such a microprocessorexecutes a program called an operating system, of which WindowsNT,Windows95 or 98, UNIX, Linux, DOS, VMS, MacOS and OS8 are examples,which controls the execution of other computer programs and providesscheduling, debugging, input/output control, accounting, compilation,storage assignment, data management and memory management, andcommunication control and related services. The processor and operatingsystem define a computer platform for which application programs inhigh-level programming languages are written.

A memory system typically includes a computer readable and writeablenonvolatile recording medium, of which a magnetic disk, a flash memoryand tape are examples. The disk may be removable, for example, a floppydisk or a read/write CD, or permanent, known as a hard drive. A disk hasa number of tracks in which signals are stored, typically in binaryform, i.e., a form interpreted as a sequence of one and zeros. Suchsignals may define an application program to be executed by themicroprocessor, or information stored on the disk to be processed by theapplication program. Typically, in operation, the processor causes datato be read from the nonvolatile recording medium into an integratedcircuit memory element, which is typically a volatile, random accessmemory such as a dynamic random access memory (DRAM) or static memory(SRAM). The integrated circuit memory element allows for faster accessto the information by the processor than does the disk. The processorgenerally manipulates the data within the integrated circuit memory andthen copies the data to the disk after processing is completed. Avariety of mechanisms are known for managing data movement between thedisk and the integrated circuit memory element, and the invention is notlimited thereto. The invention is not limited to a particular memorysystem.

Such a system may be implemented in software or hardware or firmware, ora combination of the three. The various elements of the system, eitherindividually or in combination may be implemented as a computer programproduct tangibly embodied in a machine-readable storage device forexecution by a computer processor. Various steps of the process may beperformed by a computer processor executing a program tangibly embodiedon a computer-readable medium to perform functions by operating on inputand generating output. Computer programming languages suitable forimplementing such a system include procedural programming languages,object-oriented programming languages, and combinations of the two.

The xrf processing module is not limited to a particular computerplatform, particular processor, or particular programming language.Additionally, the computer system may be a multi processor computersystem or may include multiple computers connected over a computernetwork. Steps 61-69 of FIG. 6 may be separate modules of a computerprogram, or may be separate computer programs. Such modules may beoperable on separate computers.

Additional Embodiments

In practice, instead of using a single detector, multiple x-raydetectors can be arrayed across a feed path to give readings of multipleitems fed side-by-side along the feed path in order to increasethroughput and/or decrease placement requirements. The x-ray detectorsmay sense fluorescence from items which are irradiated by a commonexcitation source or individual excitation sources. In this arrangement,it may be (but is not necessarily) preferable to perform a binary sort(as in the NRT VinylCycle) instead of sequential multiple sorts.

One of the surprise discoveries is that we found that aluminum samplesfrom automobile scrap can be identified by the sorting system. This isan unexpected result that we did not earlier anticipate. Aluminum itselfis not detectable by our experimental system since it fluoresces only aKα emission at 1.49 kev and a Kβ emission and 1.55 kev. These low energyx-rays are readily absorbed in air before they can reach the detectionsystem. Therefore, we had proposed that the unit could be used to detectthe heavier nonferrous metals letting aluminum flow through undetected.However, when we looked at an aluminum sample with our detection system,we found a strong spectrum which we identified as belonging to thealloying metals in the aluminum.

In initial profiling of the aluminum samples, we noticed three types ofalloys present in the samples. In order to test the ability of thesystem to recognize aluminum by alloy type we picked a representativesample from each of the three types to use as a reference material andgenerated a reference fluorescence spectrum from each of them. One ofthe reference spectra represented the predominant number of samples inour sample group. We went back into the original sample and selected anadditional six samples having the other spectra so that we had twentysamples of one alloy type, AL13B, four samples of type AL6B, and foursamples of type ALC1B. We then loaded the three reference spectra into aprototype sorter and ran the twenty-eight samples through the sorterfive times each to determine if they could be identified by alloy type.We used the same system settings as for the earlier prior tests.

We found that our system had the ability to separate one non-ferrousmetal from a group of metals, and also the ability to recover and sortone alloy of non-ferrous metals from all other alloys and groups ofnon-ferrous metals. This result can be extended to recovery of severaldifferent alloys at the same time by using multiple sensing andseparation channels within a single machine. Technologies exist toidentify non-ferrous metals and alloys, but they are slow. No rapidsorting technology is in existence today to accomplish sortation ofmetallic alloys. Thus, separation of alloys at rapid speeds representsan entirely new commercial opportunity.

Having now described some illustrative embodiments, it should beapparent to those skilled in the art that the foregoing is merelyillustrative and not limiting, having been presented by way of exampleonly. Numerous modifications and other illustrative embodiments arewithin the scope of one of ordinary skill in the art and arecontemplated as falling within the scope of the invention. Inparticular, although many of the examples presented herein involvespecific combinations of method steps or apparatus elements, it shouldbe understood that those steps and those elements may be combined inother ways to accomplish the same objectives. Steps, elements andfeatures discussed only in connection with one embodiment are notintended to be excluded from a similar role in other embodiments.

1. A method, comprising: irradiating an object with x-rays using anx-ray source, the object having an unknown material composition;detecting x-rays fluoresced from the object in response to irradiatingthe object with x-rays, using an x-ray detector; determining an x-rayfluorescence spectrum from the x-rays detected by the x-ray detector;recognizing a spectral pattern in the x-ray fluorescence spectrum; andclassifying the object based on the spectral pattern, wherein detecting,determining, recognizing and classifying are cumulatively performed inless than one second.